845 resultados para All-cause survival
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Objective: Burnout, a psychological consequence of prolonged work stress, has been shown to coexist with physical and mental disorders. The aim of this study was to investigate whether burnout is related to all-cause mortality among employees. Methods: In 1996, of 15,466 Finnish forest industry employees, 9705 participated in the 'Still Working' study and 8371 were subsequently identified from the National Population Register. Those who had been treated in a hospital for the most common causes of death prior to the assessment of burnout were excluded on the basis of the Hospital Discharge Register, resulting in a final study population of 7396 people. Burnout was measured using the Maslach Burnout Inventory-General Survey. Dates of death from 1996 to 2006 were extracted from the National Mortality Register. Mortality was predicted with Cox hazard regression models, controlling for baseline sociodemographic factors and register-based health status according to entitled medical reimbursement and prescribed medication for mental health problems, cardiac risk factors, and pain problems. Results: During the 10-year 10-month follow-up, a total of 199 employees had died. The risk of mortality per one-unit increase in burnout was 35% higher (95% CI 1.07-1.71) for total score and 26% higher (0.99-1.60) for exhaustion, 29% higher for cynicism (1.03-1.62), and 22% higher for diminished professional efficacy (0.96-1.55) in participants who had been under 45 at baseline. After adjustments, only the associations regarding burnout and exhaustion were statistically significant. Burnout was not related to mortality among the older employees. Conclusion: Burnout, especially work-related exhaustion, may be a risk for overall survival. (C) 2010 Elsevier Inc. All rights reserved.
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Objective To investigate the association between periodontitis and mortality from all causes in a prospective study in a homogenous group of 60- to 70-year-old West European men. Methodology A representative sample of 1400 dentate men, (mean age 63.8, SD 3.0 years), drawn from the population of Northern Ireland, had a comprehensive periodontal examination between 2001 and 2003. Men were divided into thirds on the basis of their mean periodontal attachment loss (PAL). The primary endpoint, death from any cause, was analysed using Kaplan-Meier survival plots and Cox's proportional hazards model. Results In total, 152 (10.9%) of the men died during a mean follow-up of 8.9 (SD 0.7) years; 37 (7.9%) men in the third with the lowest PAL (<1.8 mm) died compared with 73 (15.7%) in the third with the highest PAL (>2.6 mm). The unadjusted hazard ratio (HR) for death in the men with the highest level of PAL compared with those with the lowest PAL was 2.11 (95% CI 1.42-3.14), p < 0.0001. After adjustment for confounding variables (age, smoking, hypertension, BMI, diabetes, cholesterol, education, marital status and previous history of a cardiovascular event) the HR was 1.57 (1.04-2.36), p = 0.03. Conclusion The European men in this prospective cohort study with the most severe loss of periodontal attachment were at an increased risk of death compared with those with the lowest loss of periodontal attachment.
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Background and Purpose-The aim was to investigate prospectively the all-cause mortality risk up to and after coronary heart disease (CHD) and stroke events in European middle-aged men.
Methods-The study population comprised 10 424 men 50 to 59 years of age recruited between 1991 and 1994 in France (N=7855) and Northern Ireland (N=2747) within the Prospective Epidemiological Study of Myocardial Infarction. Incident CHD and stroke events and deaths from all causes were prospectively registered during the 10-year follow-up. In Cox's proportional hazards regression analysis, CHD and stroke events during follow-up were used as time-dependent covariates.
Results-A total of 769 CHD and 132 stroke events were adjudicated, and 569 deaths up to and 66 after CHD or stroke occurred during follow-up. After adjustment for study country and cardiovascular risk factors, the hazard ratios of all-cause mortality were 1.58 (95% confidence interval 1.18-2.12) after CHD and 3.13 (95% confidence interval 1.98-4.92) after stroke.
Conclusions-These findings support continuous efforts to promote both primary and secondary prevention of cardiovascular disease.
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BACKGROUND Mortality risk for people with chronic kidney disease is substantially greater than that for the general population, increasing to a 7-fold greater risk for those on dialysis therapy. Higher body mass index, generally due to higher energy intake, appears protective for people on dialysis therapy, but the relationship between energy intake and survival in those with reduced kidney function is unknown. STUDY DESIGN Prospective cohort study with a median follow-up of 14.5 (IQR, 11.2-15.2) years. SETTING & PARTICIPANTS Blue Mountains Area, west of Sydney, Australia. Participants in the general community enrolled in the Blue Mountains Eye Study (n=2,664) who underwent a detailed interview, food frequency questionnaire, and physical examination including body weight, height, blood pressure, and laboratory tests. PREDICTORS Relative energy intake, food components (carbohydrates, total sugars, fat, protein, and water), and estimated glomerular filtration rate (eGFR). Relative energy intake was dichotomized at 100%, and eGFR, at 60mL/min/1.73m(2). OUTCOMES All-cause and cardiovascular mortality. MEASUREMENTS All-cause and cardiovascular mortality using unadjusted and adjusted Cox proportional regression models. RESULTS 949 people died during follow-up, 318 of cardiovascular events. In people with eGFR<60mL/min/1.73m(2) (n=852), there was an increased risk of all-cause mortality (HR, 1.48; P=0.03), but no increased risk of cardiovascular mortality (HR, 1.59; P=0.1) among those with higher relative energy intake compared with those with lower relative energy intake. Increasing intake of carbohydrates (HR per 100g/d, 1.50; P=0.04) and total sugars (HR per 100g/d, 1.62; P=0.03) was associated significantly with increased risk of cardiovascular mortality. LIMITATIONS Under-reporting of energy intake, baseline laboratory and food intake values only, white population. CONCLUSIONS Increasing relative energy intake was associated with increased all-cause mortality in patients with eGFR<60mL/min/1.73m(2). This effect may be mediated by increasing total sugars intake on subsequent cardiovascular events.
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BACKGROUND Little is known as to whether negative emotions adversely impact the prognosis of patients who undergo cardiac rehabilitation. We prospectively investigated the predictive value of state negative affect (NA) assessed at discharge from cardiac rehabilitation for prognosis and the moderating role of positive affect (PA) on the effect of NA on outcomes. METHODS A total of 564 cardiac patients (62.49 ± 11.51) completed a comprehensive three-month outpatient cardiac rehabilitation program, filling in the Global Mood Scale (GMS) at discharge. The combined endpoint was cardiovascular disease (CVD)-related hospitalizations plus all-cause mortality at follow-up. Cox regression models estimated the predictive value of NA, as well as the moderating influence of PA on outcomes. Survival models were adjusted for sociodemographic factors, traditional cardiovascular risk factors, and severity of disease. RESULTS During a mean follow-up period of 3.4 years, 71 patients were hospitalized for a CVD-related event and 15 patients died. NA score (range 0-20) was a significant and independent predictor (hazard ratio (HR) 1.091, 95% confidence interval (CI) 1.012-1.175; p = 0.023) with a three-point higher level in NA increasing the relative risk by 9.1%. Furthermore, PA interacted significantly with NA (p < 0.001). The relative risk of poor prognosis with NA was increased in patients with low PA (p = 0.012) but remained unchanged in combination with high PA (p = 0.12). CONCLUSION The combination of NA with low PA was particularly predictive of poor prognosis. Whether reduction of NA and increase of PA, particularly in those with high NA, improves outcome needs to be tested.
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Background To explore the impact of geographical remoteness and area-level socioeconomic disadvantage on colorectal cancer (CRC) survival. Methods Multilevel logistic regression and Markov chain Monte Carlo simulations were used to analyze geographical variations in five-year all-cause and CRC-specific survival across 478 regions in Queensland Australia for 22,727 CRC cases aged 20–84 years diagnosed from 1997–2007. Results Area-level disadvantage and geographic remoteness were independently associated with CRC survival. After full multivariate adjustment (both levels), patients from remote (odds Ratio [OR]: 1.24, 95%CrI: 1.07-1.42) and more disadvantaged quintiles (OR = 1.12, 1.15, 1.20, 1.23 for Quintiles 4, 3, 2 and 1 respectively) had lower CRC-specific survival than major cities and least disadvantaged areas. Similar associations were found for all-cause survival. Area disadvantage accounted for a substantial amount of the all-cause variation between areas. Conclusions We have demonstrated that the area-level inequalities in survival of colorectal cancer patients cannot be explained by the measured individual-level characteristics of the patients or their cancer and remain after adjusting for cancer stage. Further research is urgently needed to clarify the factors that underlie the survival differences, including the importance of geographical differences in clinical management of CRC.
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Background Up-to-date evidence on levels and trends for age-sex-specific all-cause and cause-specific mortality is essential for the formation of global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013) we estimated yearly deaths for 188 countries between 1990, and 2013. We used the results to assess whether there is epidemiological convergence across countries. Methods We estimated age-sex-specific all-cause mortality using the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data. We generally estimated cause of death as in the GBD 2010. Key improvements included the addition of more recent vital registration data for 72 countries, an updated verbal autopsy literature review, two new and detailed data systems for China, and more detail for Mexico, UK, Turkey, and Russia. We improved statistical models for garbage code redistribution. We used six different modelling strategies across the 240 causes; cause of death ensemble modelling (CODEm) was the dominant strategy for causes with sufficient information. Trends for Alzheimer's disease and other dementias were informed by meta-regression of prevalence studies. For pathogen-specific causes of diarrhoea and lower respiratory infections we used a counterfactual approach. We computed two measures of convergence (inequality) across countries: the average relative difference across all pairs of countries (Gini coefficient) and the average absolute difference across countries. To summarise broad findings, we used multiple decrement life-tables to decompose probabilities of death from birth to exact age 15 years, from exact age 15 years to exact age 50 years, and from exact age 50 years to exact age 75 years, and life expectancy at birth into major causes. For all quantities reported, we computed 95% uncertainty intervals (UIs). We constrained cause-specific fractions within each age-sex-country-year group to sum to all-cause mortality based on draws from the uncertainty distributions. Findings Global life expectancy for both sexes increased from 65·3 years (UI 65·0–65·6) in 1990, to 71·5 years (UI 71·0–71·9) in 2013, while the number of deaths increased from 47·5 million (UI 46·8–48·2) to 54·9 million (UI 53·6–56·3) over the same interval. Global progress masked variation by age and sex: for children, average absolute differences between countries decreased but relative differences increased. For women aged 25–39 years and older than 75 years and for men aged 20–49 years and 65 years and older, both absolute and relative differences increased. Decomposition of global and regional life expectancy showed the prominent role of reductions in age-standardised death rates for cardiovascular diseases and cancers in high-income regions, and reductions in child deaths from diarrhoea, lower respiratory infections, and neonatal causes in low-income regions. HIV/AIDS reduced life expectancy in southern sub-Saharan Africa. For most communicable causes of death both numbers of deaths and age-standardised death rates fell whereas for most non-communicable causes, demographic shifts have increased numbers of deaths but decreased age-standardised death rates. Global deaths from injury increased by 10·7%, from 4·3 million deaths in 1990 to 4·8 million in 2013; but age-standardised rates declined over the same period by 21%. For some causes of more than 100 000 deaths per year in 2013, age-standardised death rates increased between 1990 and 2013, including HIV/AIDS, pancreatic cancer, atrial fibrillation and flutter, drug use disorders, diabetes, chronic kidney disease, and sickle-cell anaemias. Diarrhoeal diseases, lower respiratory infections, neonatal causes, and malaria are still in the top five causes of death in children younger than 5 years. The most important pathogens are rotavirus for diarrhoea and pneumococcus for lower respiratory infections. Country-specific probabilities of death over three phases of life were substantially varied between and within regions. Interpretation For most countries, the general pattern of reductions in age-sex specific mortality has been associated with a progressive shift towards a larger share of the remaining deaths caused by non-communicable disease and injuries. Assessing epidemiological convergence across countries depends on whether an absolute or relative measure of inequality is used. Nevertheless, age-standardised death rates for seven substantial causes are increasing, suggesting the potential for reversals in some countries. Important gaps exist in the empirical data for cause of death estimates for some countries; for example, no national data for India are available for the past decade.
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Background Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival. Methods Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20–84 years diagnosed during 1997–2007 from Queensland, Australia. Results Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the between-area variability in survival using multilevel discrete-time models was no longer significant. Spatial inequalities in survival were also markedly reduced after adjusting for aggregated area-level covariates. Only the multilevel approach however, provided an estimation of the contribution of geographical variation to the total variation in survival between individual patients. Conclusions With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from international settings
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Background Studies of mid-aged adults provide evidence of a relationship between sitting-time and all-cause mortality, but evidence in older adults is limited. The aim is to examine the relationship between total sitting-time and all-cause mortality in older women. Methods The prospective cohort design involved 6656 participants in the Australian Longitudinal Study on Women's Health who were followed for up to 9 years (2002, age 76–81, to 2011, age 85–90). Self-reported total sitting-time was linked to all-cause mortality data from the National Death Index from 2002 to 2011. Cox proportional hazard models were used to examine the relationship between sitting-time and all-cause mortality, with adjustment for potential sociodemographic, behavioural and health confounders. Results There were 2003 (30.1%) deaths during a median follow-up of 6 years. Compared with participants who sat <4 h/day, those who sat 8–11 h/day had a 1.45 times higher risk of death and those who sat ≥11 h/day had a 1.65 times higher risk of death. These risks remained after adding sociodemographic and behavioural covariates, but were attenuated after adjustment for health covariates. A significant interaction (p=0.02) was found between sitting-time and physical activity (PA), with increased mortality risk for prolonged sitting only among participants not meeting PA guidelines (HR for sitting ≥8 h/day: 1.31, 95% CI 1.07 to 1.61); HR for sitting ≥11 h/day: 1.47, CI 1.15 to 1.93). Conclusions Prolonged sitting-time was positively associated with all-cause mortality. Women who reported sitting for more than 8 h/day and did not meet PA guidelines had an increased risk of dying within the next 9 years.
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We examined the association between workplace social capital and all-cause mortality in a large occupational cohort from Finland.